Orchestrating the Agentic Symphony: A Deep Dive into DDD-Driven Microservice Independence

Building a single AI agent is a weekend project. Building a production-grade Agentic Suite that scales, adapts, and survives the fast-moving LLM landscape is a systematic engineering challenge. At Berlin AI Labs, we recently completed a major refactoring of our entire ecosystem—what we now call the "Berlin AI Orchestra". By applying Domain-Driven Design (DDD) and Hexagonal Architecture, we've successfully decoupled our core logic into a set of 100% independent microservices.

The Cacophony of Coupling

Most agentic systems start as "Smart Wrappers"—monoliths where the business logic, LLM prompts, and infrastructure (like Cloudinary or vector DBs) are tightly braided. This is fine for a MVP, but in a multi-model, multi-platform environment, it becomes a maintenance nightmare.

When we extracted our Compliance Engine, we hit a classic architectural wall: the library was still importing the Conversation entity from the host application. In musical terms, our violinist was trying to read the pianist's sheet music. It worked, but you couldn't take the violinist to another gig without bringing the piano along.

Developing the Score: Bounded Contexts & Ubiquitous Language

The first step in DDD is identifying Bounded Contexts. A "Conversation" in a mental health chatbot has different invariants than a "Conversation" in a marketing reel generator. However, for our AgentOps Suite, we needed a shared vocabulary—a Ubiquitous Language.

We defined a core Conversation entity and, crucially, internalized it within each library. By moving the entity definition into src/lib//domain/entities/, we turned a cross-boundary dependency into a self-contained domain motif.

// The Motif: Internalized Domain Entity
export interface ConversationMessage {
    role: 'user' | 'assistant' | 'system';
    content: string;
    timestamp: Date;
}

export interface Conversation {
    id: string;
    messages: ConversationMessage[];
    metadata: Record<string, any>;
}

The Orchestra Sections: Decoupled Microservices

With the domain boundaries set, we extracted five core pillars of our Agentic Symphony:

• The Woodwinds (Semantic Aligner): Solves the "Ontology Mismatch" problem. It uses ZK-proofs to verify that messages align with specific semantic schemas without exposing the full content.
• The Strings (Fairness Auditor): A real-time auditing service that monitors interactions for bias and toxicity, keeping the performance ethical.
• The Percussion (Deadline Enforcer): Monitors SLA compliance. If an agent misses a beat (timeout or latency spike), the enforcer triggers an intervention.
• The Conductor (Capability Broker): A dynamic discovery service that routes tasks to the most efficient agent based on real-time availability and specialized scores.

Hexagonal Architecture: Ports & Adapters

To ensure 100% portability, we strictly followed Hexagonal Architecture (Ports & Adapters). The domain logic (the "Inner Core") defines Ports (interfaces) for everything it needs from the outside world.

Whether we use OpenRouter, Beam.cloud, or a local Llama-3 instance, the domain logic remains oblivious. We simply swap out the Adapters. This is how we managed to switch our image generation from DALL-E 3 to FLUX.1 on Beam.cloud without rewriting a single line of our promotional engine logic.

Verification: Characterization Tests

You don't refactor an orchestra while they're playing a concert without a safety net. Before moving any code, we wrote Characterization Tests—lock-in tests that record the current behavior of the system.

We achieved zero regressions across 305+ tests by ensuring that the new decoupled libraries produced the exact same "sound" as the integrated ones. We even integrated Playwright for E2E verification, ensuring that the final "performance" (the generated video or compliance audit) remained flawless.

Conclusion: The Future of Agentic Infrastructure

As the Agentic Economy matures, the winners won't be those with the smartest single prompt, but those with the most composable infrastructure. By applying DDD and architectural patterns usually reserved for high-scale enterprise systems, we've built a suite that is ready for the "cacophony" of the real world.

At Berlin AI Labs, we're not just building agents; we're composing the future of automated intelligence. If you're interested in building scalable, auditable, and truly independent AI systems, let's talk shop.